Design optimisation and characterisation of an amperometric glutamate oxidase-based composite biosensor for neurotransmitter l-glutamic acid.

A polymer/enzyme composite biosensor for monitoring neurochemical glutamate was performance optimised in vitro for sensitivity, selectivity and stability. This first generation Pt/glutamate oxidase-based sensor displayed appropriate sensitivity (90.4 ± 2.0 nA cm-2 µM-1). It also has ideal stability/biocompatibility with no significant decrease in response observed for repeated calibrations, exposure to electron beam sterilisation, or following storage at 4 °C either dry (28 days) or in ex-vivo rodent brain tissue (14 days). Potential non-glutamate contributing signals, generated by extracellular levels of the principal endogenous electroactive interferents, were typically <5% of the basal (10 µM) glutamate response. Changes in molecular oxygen (the natural enzyme mediator) over the normal brain tissue range of 40-80 µM had minimal effect on the glutamate signal for concentrations of 10 and 100 µM (Mean KMO2 = 1.86 ± 0.74 µM, [O2]90% = ca. 15 µM). Additionally, a low µM calculated limit of detection (0.44 ± 0.05) and rapid response time (ca. 1.67 ± 0.06 s), combined with no effect of pH and temperature changes over physiologically relevant ranges (7.2-7.6 and 34-40 °C respectively), collectively suggest that this composite biosensor should reliably detect l-glutamate when used for neurochemical monitoring. Preliminary experiments involving implantation in the striatum of freely moving rats demonstrated stable recording over several weeks, and reliable detection of physiological changes in glutamate in response to behavioural/neuronal activation (locomotor activity and restraint stress).

Development and validation of a real-time microelectrochemical sensor for clinical monitoring of tissue oxygenation/perfusion.

Oxygen is of critical importance to tissue viability and there is increasing demand for its reliable real-time clinical monitoring in order to prevent, diagnose, and treat several pathological disorders, including hypoxia, stroke and reperfusion injury. Herein we report the development and characterisation of a prototype clinical O2 sensor, and its validation in vivo, including proof-of-concept monitoring in patients undergoing surgery for carpal tunnel release. An integrated platinum-based microelectrochemical device was custom designed and controlled using a miniaturised telemetry-operated single channel clinical potentiostat. The in vitro performance of different sensor configurations is presented, with the best sensor design (S2) displaying appropriate linearity (R2 = 0.994) and sensitivity (0.569 ± 0.022 nA µM-1). Pre-clinical validation of S2 was performed in the hind limb muscle of anaesthetised rats; tourniquet application resulted in a significant rapid decrease in signal (90 ± 27%, [ΔO2] ca. 140 ± 18 µM), with a return to baseline within a period of ca. 3 min following tourniquet release. Similar trends were observed in the clinical study; an immediate decrease in signal (39 ± 3%, [ΔO2] ca. 30 ± 20 µM), with basal levels re-established within 2 min of tourniquet release. These results confirm that continuous real-time monitoring of dynamic changes in tissue O2 can serve as an indicator of reperfusion status in patients undergoing carpal tunnel surgery, and suggests the potential usefulness of the developed microelectrochemical sensor for other medical conditions where clinical monitoring of O2 and perfusion is important.

Multicomponent analysis using a confocal Raman microscope.

Measuring the concentration of multiple chemical components in a low-volume aqueous mixture by Raman spectroscopy has received significant interest in the literature. All of the contributions to date focus on the design of optical systems that facilitate the recording of spectra with high signal-to-noise ratio by collecting as many Raman scattered photons as possible. In this study, the confocal Raman microscope setup is investigated for multicomponent analysis. Partial least-squares regression is used to quantify physiologically relevant aqueous mixtures of glucose, lactic acid, and urea. The predicted error is 17.81 mg/dL for glucose, 10.6 mg/dL for lactic acid, and 7.6 mg/dL for urea, although this can be improved with increased acquisition times. A theoretical analysis of the method is proposed, which relates the numerical aperture and the magnification of the microscope objective, as well as the confocal pinhole size, to the performance of the technique.